AI Agents, Meet Test Driven Development
Anita • Gen Growth & Education Lead, Vum
Drawing from experience working with hundreds of companies deploying AI in production, Anita demonstrates why test-driven development is non-negotiable for reliable AI agent systems. Introduces the L0-L4 agentic workflow framework and delivers a live SEO agent demo achieving 60% performance improvement through TDD practices.
"The more agents you have the more important it becomes to have tests because you need to know which agent is failing and what exactly is going wrong."Anita, Vum (00:13:48)
Executive Summary
As AI systems evolve from simple prompt chaining to complex multi-agent architectures, the need for rigorous testing becomes paramount. Anita introduces the L0-L4 agentic workflow framework, a comprehensive model for understanding AI system complexity and implementing appropriate testing strategies at each level.
Through a live SEO agent demonstration, the talk shows how test-driven development enables teams to build robust, maintainable AI systems. The demo features a four-component workflow (SEO Analyst, Researcher, Writer, Editor) that leverages evaluation loops to achieve 60% performance improvement while maintaining quality consistency.
The presentation culminates with Bellum Workflows (now Workflow SDK), an open-source tool designed to help engineering teams build AI systems while maintaining test-driven practices, with a self-documenting syntax that keeps UI and code in perfect sync.
The L0-L4 Agentic Workflow Framework
A comprehensive model for understanding AI system complexity and implementing appropriate testing strategies
L0: Basic Prompt Chaining
Classic GPT-style prompt sequences. Simple chains where prompts are executed sequentially.
"L0 is where you're just chaining prompts together, it's like your classic GPT chain."
00:22:00L1: Simple Agent
Single agent with basic capabilities. The first step beyond static prompting.
L2: Multi-Agent Coordination
Multiple agents working together with human oversight. Agents begin to specialize but still require human intervention.
"L2 is where you start having multiple agents working together but they still require a bit of human oversight."
00:29:36L3: Self-Correcting Agents with Evaluation Loops
Agents can self-correct and iterate through automated evaluation loops. Quality gates maintain consistency across iterations.
"L3 is where you start having your own evaluator loops, your agents can self-correct and iterate."
00:34:88L4: Fully Autonomous Systems
Agents that can learn and adapt independently. The highest level of agentic capability with continuous learning.
"L4 is fully autonomous systems where your agents can learn and adapt on their own."
00:38:40Why Testing Complexity Scales with Agents
As systems progress from L0 to L4, testing becomes increasingly critical. With multiple agents working in parallel, you need comprehensive tests to identify:
- Which specific agent is failing
- What exactly is going wrong in the workflow
- Where quality is being compromised
- How to maintain consistency across iterations
SEO Agent Demo: 60% Performance Improvement
A live demonstration showing how test-driven development and evaluation loops dramatically improve AI system performance
Performance Improvement with TDD
300s (baseline) → 118s (optimized)60% faster
Four-Agent SEO Workflow Architecture
SEO Analyst
Analyzes top-performing articles to identify SEO patterns and ranking factors
Researcher
Identifies content gaps and research opportunities based on competitive analysis
Writer
Creates content based on research findings and SEO requirements
Editor
Iteratively improves quality through evaluator loops and self-correction
"This usually takes around 300 seconds to run when we have more evaluation Loops but it's pretty great. And it saves me a lot of my time."27:42 - Live Demo Results
Test-Driven Development for AI Agents
Key principles and practices from hundreds of production AI deployments
Start with Your Level
Use the L0-L4 framework to assess your current AI system complexity and implement appropriate testing strategies.
Don't over-engineer tests for simple L0 systems, but ensure comprehensive coverage for L3-L4 autonomous systems.
Implement Evaluator Loops
For systems beyond L1, implement automated evaluation loops to maintain quality consistency across iterations.
"The evaluator loops are what help you maintain quality and consistency across different iterations."
Give Developers Control
Empower your engineering team with tools that allow them to define workflows in their preferred codebase environment.
"More code developers want more control and flexibility and they want to own their definitions in their codebase."
Top Quotes from the Talk
Verbatim insights on test-driven development, agent frameworks, and production AI
"Over the last few years we worked with hundreds of companies who have successfully deployed reliable AI Solutions in production from simple to more advanced agentic workflows."
"One thing became clear those companies who have adopted a test driven development approach were able to build reliable and stronger systems."
"If you look at 2023, AI was just about prompt chaining and then came reinforcement learning from human feedback and then we got Chain of Thought and then we got more agents."
"We came up with a framework that helps you understand what level of agentic workflow you're in and what kind of testing approach you should be following."
"L0 is where you're just chaining prompts together, it's like your classic GPT chain."
"L2 is where you start having multiple agents working together but they still require a bit of human oversight."
"L3 is where you start having your own evaluator loops, your agents can self-correct and iterate."
"L4 is fully autonomous systems where your agents can learn and adapt on their own."
"The evaluator loops are what help you maintain quality and consistency across different iterations."
"This usually takes around 300 seconds to run when we have more evaluation Loops but it's pretty great."
Actionable Insights
Practical guidance for implementing test-driven development in your AI agent workflows
TDD is Non-Negotiable
Essential for reliability and maintainability
- •Test-driven development becomes essential as complexity grows
- •Without tests, identifying failure points becomes impossible
- •TDD enables confident iteration on agent systems
Use a Framework-Based Approach
The L0-L4 framework for appropriate testing strategies
- •Understand your current state and complexity level
- •Implement testing strategies appropriate to your level
- •Progress systematically from basic to advanced patterns
Implement Evaluator Loops
Automated evaluation for quality consistency
- •For systems beyond L1, implement automated evaluation loops
- •Maintain quality consistency across iterations
- •Enable self-correction through continuous feedback
Give Developers Control
Flexibility in preferred codebase
- •Successful AI development requires developer control
- •Allow flexibility to define workflows
- •Support custom codebases and configurations
Iterate on Quality
Continuous improvement over time
- •Don't aim for perfection in the first iteration
- •Use evaluator loops to continuously improve
- •Focus on incremental enhancements to AI system performance
Leverage Open Source Tools
Accelerate development with test-driven practices
- •Consider open-source tools like Workflow SDK
- •Accelerate AI development while maintaining quality
- •Balance speed with rigorous testing practices
Key Video Timestamps
Jump to specific sections of the talk
AI Agents, Meet Test Driven Development
Speaker: Anita, Gen Growth & Education Lead at Vum
Duration: ~29 minutes
Event: AI Engineers Conference